def test_string_max_length_validation(self):
with self.assertRaisesRegex(ValueError, 'string_max_length'):
iblt_factory.IbltFactory(string_max_length=0,
capacity=10,
repetitions=3,
seed=0)
with self.assertRaisesRegex(ValueError, 'string_max_length'):
iblt_factory.IbltFactory(string_max_length=-1,
capacity=10,
repetitions=3,
seed=0)
# Should not raise
iblt_factory.IbltFactory(string_max_length=1,
capacity=10,
repetitions=3,
seed=0)
def test_iblt_aggregation_as_expected(
self,
capacity: int,
string_max_length: int,
repetitions: int,
seed: int,
sketch_agg_factory: Optional[
factory.UnweightedAggregationFactory] = None,
value_tensor_agg_factory: Optional[
factory.UnweightedAggregationFactory] = None):
iblt_agg_factory = iblt_factory.IbltFactory(
sketch_agg_factory=sketch_agg_factory,
value_tensor_agg_factory=value_tensor_agg_factory,
capacity=capacity,
string_max_length=string_max_length,
repetitions=repetitions,
seed=seed)
iblt_agg_process = iblt_agg_factory.create(VALUE_TYPE)
process_output = iblt_agg_process.next(iblt_agg_process.initialize(),
CLIENT_DATA)
output_strings = [
s.decode('utf-8') for s in process_output.result.output_strings
]
string_values = process_output.result.string_values
result = dict(zip(output_strings, string_values))
self.assertCountEqual(result, AGGREGATED_DATA)
expected_measurements = collections.OrderedDict([('num_not_decoded',
0), ('sketch', ()),
('value_tensor', ())])
self.assertCountEqual(process_output.measurements,
expected_measurements)
def test_value_type_validation(self, value_type):
iblt_agg_factory = iblt_factory.IbltFactory(capacity=10,
string_max_length=5,
repetitions=3,
seed=0)
with self.assertRaises(ValueError):
iblt_agg_factory.create(value_type)
def test_repetitions_validation(self):
with self.assertRaisesRegex(ValueError, 'repetitions'):
iblt_factory.IbltFactory(repetitions=0,
capacity=10,
string_max_length=10,
seed=0)
with self.assertRaisesRegex(ValueError, 'repetitions'):
iblt_factory.IbltFactory(repetitions=2,
capacity=10,
string_max_length=10,
seed=0)
# Should not raise
iblt_factory.IbltFactory(repetitions=3,
capacity=10,
string_max_length=10,
seed=0)
def test_string_max_length_error(self):
client = collections.OrderedDict([
(iblt_factory.DATASET_KEY,
tf.constant(['thisisalongword'], dtype=tf.string)),
(iblt_factory.DATASET_VALUE, tf.constant([[1]], dtype=tf.int64)),
])
value_type = computation_types.SequenceType(
collections.OrderedDict(key=tf.string,
value=computation_types.TensorType(
shape=(1, ), dtype=tf.int64)))
client_data = [tf.data.Dataset.from_tensor_slices(client)]
iblt_agg_factory = iblt_factory.IbltFactory(capacity=10,
string_max_length=5,
repetitions=3,
seed=0)
iblt_agg_process = iblt_agg_factory.create(value_type)
with self.assertRaises(tf.errors.InvalidArgumentError):
iblt_agg_process.next(iblt_agg_process.initialize(), client_data)